{"id":"W1984467618","doi":"10.4018/ijkbo.2012100103","title":"Ontology Merging and Reasoning Using Paraconsistent Logics","year":2012,"lang":"en","type":"article","venue":"International Journal of Knowledge-Based Organizations","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Ontology; Computer science; Consistency (knowledge bases); Paraconsistent logic; Perspective (graphical); Description logic; Process (computing); Artificial intelligence; Theoretical computer science; Epistemology; Programming language; Higher-order logic","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007364986,0.0006547209,0.0008648501,0.002584202,0.002186656,0.004499845,0.003364775,0.001836647,0.003311271],"category_scores_gemma":[0.01485976,0.001084653,0.00194659,0.002655118,0.002327971,0.007968412,0.005214565,0.002775519,0.0006730067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002179391,"about_ca_system_score_gemma":0.002634938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00414648,"about_ca_topic_score_gemma":0.00581173,"domain_scores_codex":[0.992657,0.002877748,0.0006363485,0.0008306124,0.002669675,0.000328497],"domain_scores_gemma":[0.990912,0.005531759,0.0008681791,0.001428208,0.001031496,0.0002283525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003852442,0.0002647862,0.001627735,0.0003518268,0.0002403547,0.001137813,0.001800843,0.1020688,0.009641747,0.6657376,0.004607159,0.2121362],"study_design_scores_gemma":[0.00008355684,0.0000455987,0.000159239,0.00004459043,0.00006652387,0.0002584441,0.000274743,0.406448,0.008519105,0.5743442,0.0097095,0.00004648422],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01091711,0.0001853892,0.9844794,0.0005238707,0.00003276977,0.00009894206,0.00007605006,0.0007317057,0.002954804],"genre_scores_gemma":[0.1671681,0.0002746039,0.8299935,0.0002601264,0.0000487394,0.0001214003,0.0003409409,0.0001214395,0.001670975],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007364986,"threshold_uncertainty_score":0.03895026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02594590843037359,"score_gpt":0.3004306801130365,"score_spread":0.2744847716826629,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}